library(Rcpp)
library(tsne)
library(dplyr)##
## 載入套件：'dplyr'## 下列物件被遮斷自 'package:stats':
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## filter, lag## 下列物件被遮斷自 'package:base':
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## intersect, setdiff, setequal, unionlibrary(stringr)
library(MASS)##
## 載入套件：'MASS'## 下列物件被遮斷自 'package:dplyr':
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## selectlibrary(randomForest)## randomForest 4.7-1.1## Type rfNews() to see new features/changes/bug fixes.##
## 載入套件：'randomForest'## 下列物件被遮斷自 'package:dplyr':
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## combinelibrary(dplyr)
library(Rcpp)
library(caret)## 載入需要的套件：ggplot2##
## 載入套件：'ggplot2'## 下列物件被遮斷自 'package:randomForest':
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## margin## 載入需要的套件：latticelibrary(ggplot2)
library(tidytext)
library(wordcloud2)
library(ggrepel)
library(ade4)
library(factoextra)## Welcome! Want to learn more? See two factoextra-related books at https://goo.gl/ve3WBalibrary(magrittr)
library("rpart")
library("rpart.plot")
library("rattle")## 載入需要的套件：tibble## 載入需要的套件：bitops## Rattle: A free graphical interface for data science with R.
## Version 5.5.1 Copyright (c) 2006-2021 Togaware Pty Ltd.
## Type 'rattle()' to shake, rattle, and roll your data.##
## 載入套件：'rattle'## 下列物件被遮斷自 'package:randomForest':
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## importancelibrary(tidytext)
library(tidyr)##
## 載入套件：'tidyr'## 下列物件被遮斷自 'package:magrittr':
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## extractlibrary(stringr)
library(stm)## stm v1.3.6 successfully loaded. See ?stm for help.
## Papers, resources, and other materials at structuraltopicmodel.com##
## 載入套件：'stm'## 下列物件被遮斷自 'package:lattice':
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## cloudlibrary(ggpubr)
#library(stsne)
library(dplyr)
library(tidyr)
library(stringr)
library(ggplot2)
library(corrplot)## corrplot 0.92 loaded#library(dummies)
library(broom)
library(mice)##
## 載入套件：'mice'## 下列物件被遮斷自 'package:stats':
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## filter## 下列物件被遮斷自 'package:base':
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## cbind, rbindlibrary(DataExplorer)
library(gridExtra)##
## 載入套件：'gridExtra'## 下列物件被遮斷自 'package:randomForest':
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## combine## 下列物件被遮斷自 'package:dplyr':
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## combinelibrary(caret)
library(RColorBrewer)
library(missForest)
library(caTools)
library(jtools)
library(randomForest)
library(e1071)
library(ROCR)
library(klaR)
library(tidyverse)## ── Attaching packages
## ───────────────────────────────────────
## tidyverse 1.3.2 ──## ✔ readr 2.1.3 ✔ forcats 0.5.2
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ gridExtra::combine() masks randomForest::combine(), dplyr::combine()
## ✖ tidyr::extract() masks magrittr::extract()
## ✖ mice::filter() masks dplyr::filter(), stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ✖ purrr::lift() masks caret::lift()
## ✖ ggplot2::margin() masks randomForest::margin()
## ✖ MASS::select() masks dplyr::select()
## ✖ purrr::set_names() masks magrittr::set_names()library(naniar)
library(VIM)## 載入需要的套件：colorspace
## 載入需要的套件：grid
## VIM is ready to use.
##
## Suggestions and bug-reports can be submitted at: https://github.com/statistikat/VIM/issues
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## 載入套件：'VIM'
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## 下列物件被遮斷自 'package:missForest':
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## nrmse
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## 下列物件被遮斷自 'package:rattle':
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## wine
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## 下列物件被遮斷自 'package:datasets':
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## sleeplibrary(FactoMineR)##
## 載入套件：'FactoMineR'
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## 下列物件被遮斷自 'package:ade4':
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## reconstlibrary(missMDA)
library(olsrr)##
## 載入套件：'olsrr'
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## 下列物件被遮斷自 'package:MASS':
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## cement
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## 下列物件被遮斷自 'package:datasets':
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## riverslibrary(mltools)##
## 載入套件：'mltools'
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## 下列物件被遮斷自 'package:e1071':
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## skewness
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## 下列物件被遮斷自 'package:tidyr':
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## replace_nalibrary(data.table)##
## 載入套件：'data.table'
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## 下列物件被遮斷自 'package:purrr':
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## transpose
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## 下列物件被遮斷自 'package:dplyr':
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## between, first, lastlibrary(xgboost)##
## 載入套件：'xgboost'
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## 下列物件被遮斷自 'package:rattle':
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## xgboost
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## 下列物件被遮斷自 'package:dplyr':
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## slicelibrary(readr)
library(stringr)
library(caret)
library(vegan)## 載入需要的套件：permute
## Registered S3 methods overwritten by 'vegan':
## method from
## plot.rda klaR
## predict.rda klaR
## print.rda klaR
## This is vegan 2.6-4
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## 載入套件：'vegan'
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## 下列物件被遮斷自 'package:klaR':
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## rda
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## 下列物件被遮斷自 'package:caret':
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## tolerancerequire(foreign)## 載入需要的套件：foreignrequire(nnet)## 載入需要的套件：nnetrequire(reshape2)## 載入需要的套件：reshape2
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## 載入套件：'reshape2'
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## 下列物件被遮斷自 'package:data.table':
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## dcast, melt
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## smithsrequire(lubridate)## 載入需要的套件：lubridate
## 載入需要的套件：timechange
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## 載入套件：'lubridate'
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## 下列物件被遮斷自 'package:data.table':
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## hour, isoweek, mday, minute, month, quarter, second, wday, week,
## yday, year
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## 下列物件被遮斷自 'package:base':
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## date, intersect, setdiff, unionlibrary(reshape2)
library(topicmodels)
library(rgl)
library(plot3D)
library(plotly)##
## 載入套件：'plotly'
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## 下列物件被遮斷自 'package:xgboost':
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## slice
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## last_plot
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## 下列物件被遮斷自 'package:MASS':
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## select
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## 下列物件被遮斷自 'package:stats':
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## filter
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## 下列物件被遮斷自 'package:graphics':
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## layoutlibrary(compiler)
library(parallel)
library(Rtsne)
library(text2vec)##
## 載入套件：'text2vec'
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## 下列物件被遮斷自 'package:topicmodels':
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## perplexityPLOTER<- read.csv("C:\\Users\\user\\Desktop\\steam_clean_TRY.csv",header=TRUE,encoding = "UTF-8",sep = ",")
#PLOTER<- read.csv("C:\\Users\\user\\Desktop\\steam_clean.csv",header=TRUE,encoding = "UTF-8",sep = ",")
glimpse(PLOTER)## Rows: 8,808
## Columns: 18
## $ appid <int> 1227890, 1230410, 1230570, 1235140, 1236990, 1238080,…
## $ name <chr> "Summer Memories", "Chaos", "Shotgun n Zombies", "Ya…
## $ release_date <chr> "2020-06-14", "2020-04-28", "2020-02-13", "2020-11-10…
## $ english <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,…
## $ developer <chr> "Dojin Otome", "Frinky", "Brandtner", "Ryu Ga Gotoku …
## $ publisher <chr> "Kagura Games", "Frinky", "Brandtner", "SEGA", "Joey …
## $ platforms <chr> "windows", "windows", "windows;linux", "windows", "wi…
## $ required_age <int> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,…
## $ categories <chr> "Single-player;Steam Trading Cards;Steam Cloud", "Mul…
## $ genres <chr> "Adventure;RPG", "Action;Casual;Free to Play;Indie", …
## $ steamspy_tags <chr> "Sexual Content;Pixel Graphics;Anime", "Action;Indie;…
## $ achievements <int> 0, 5, 0, 63, 0, 56, 0, 34, 0, 0, 13, 20, 52, 36, 13, …
## $ positive_ratings <int> 8805, 3227, 4, 17570, 2324, 2902, 5902, 17484, 17317,…
## $ negative_ratings <int> 628, 407, 4, 718, 182, 1780, 188, 355, 466, 113, 344,…
## $ average_playtime <int> 453, 0, 0, 3342, 29, 162, 2774, 421, 27, 0, 71, 9, 56…
## $ median_playtime <int> 364, 0, 0, 2935, 25, 181, 1936, 358, 32, 0, 82, 9, 14…
## $ owners <chr> "200000-500000", "200000-500000", "200000-500000", "2…
## $ price <dbl> 318, 0, 45, 1690, 66, 539, 408, 238, 45, 399, 0, 0, 0…#PLOTER<-str_replace_all(PLOTER,"[[:punct:]]" , "_")
#PLOTER<-str_replace_all(PLOTER,"[^[:alnum:]]" , "_")
#gsub("<U\\+[0-9A-F]{4}>",'',PLOTER$name)
#PLOTER$name <- gsub("<U\\+[0-9A-F]{4}>",'',PLOTER$name)
PLOTER$name <- str_replace_all(PLOTER$name,"[[:punct:]]" , "_")
PLOTER$name <- str_replace_all(PLOTER$name,"[^[:alnum:]]" , "_")
#cleandata <- c()
#for (i in 1:length(PLOTER$name)) {
#if (grepl('<e5>',PLOTER$name[i]) == FALSE ){
# cleandata <- rbind(cleandata,PLOTER[i,])
#}
#}
#PLOTER <- PLOTER[!str_detect(PLOTER$name," " , negate = FALSE)]
PLOTER <- PLOTER[!duplicated(PLOTER$name), ]
PLOTER$developer <- str_replace_all(PLOTER$developer,"[[:punct:]]" , "_")
PLOTER$developer <- str_replace_all(PLOTER$developer,"[^[:alnum:]]" , "_")
PLOTER$publisher <- str_replace_all(PLOTER$publisher,"[[:punct:]]" , "")
PLOTER$publisher <- str_replace_all(PLOTER$publisher,"[^[:alnum:]]" , "")
PLOTER <- na.omit(PLOTER)
first_encod<- subset(PLOTER,select= -c(name,developer,publisher,appid))
#glimpse(first_encod)encoding: first_encod$release_date
#ymd(first_encod$release_date[1])
int <- interval(ymd(first_encod$release_date), ymd("2022-12-10"))
age <- scale(int_length(int))
first_encod$release_date <- age[,1]
#glimpse(first_encod)
head(first_encod)encoding:string to factor
first_encod\(genres first_encod\)owners first_encod\(steamspy_tags first_encod\)release_date first_encod$categories
#factorize <- function(dataframe){
# for (i in 1:length(dataframe)) {
# if (is.character(dataframe[,i])){
# dataframe[i] <- as.factor(dataframe[,i])
# }
# }
#}
for (i in 1:length(first_encod)) {
if (is.character(first_encod[,i])){
first_encod[i] <- as.factor(first_encod[,i])
}
}
#factorize(first_encod)
#glimpse(first_encod)
head(first_encod)first_encod one-hot
first_encod_oh <- one_hot(as.data.table(first_encod))
c(length(levels(first_encod$genres))
,length(levels(first_encod$steamspy_tags ))
,length(levels(first_encod$categories )))## [1] 823 5553 1823#prcomp(first_encod_oh)multi-value to single-value
#first_encod %>%
# mutate(steamspy_tags = str_replace_all(steamspy_tags, paste(Strategy, collapse = #"|", "$", sep = ""), "Companionship"))separate_rows
separated_data <- first_encod %>%
separate_rows(genres, sep = ";")%>%separate_rows(categories, sep = ";") %>%separate_rows(steamspy_tags, sep = ";")%>%separate_rows(platforms, sep = ";")%>%group_by(categories)%>%group_by(steamspy_tags)%>%group_by(genres)
separated_data#glimpse(separated_data)
head(separated_data)separate_rows_2
#spread(first_encod, key=categories , fill = NA, convert = FALSE)
separated_data <- first_encod %>%
separate_rows(genres, sep = ";",convert = TRUE)%>%separate_rows(categories, sep = ";") %>%separate_rows(steamspy_tags, sep = ";",convert = TRUE)%>%separate_rows(platforms, sep = ";",convert = TRUE)%>%group_by(categories)%>%group_by(steamspy_tags)%>%group_by(genres)
#head(glimpse(separated_data))separate collapsed column to muitiple column:categories
#first_encod %>% separate(categories, c("categories1", "categories2","categories3","categories4","categories5","categories6","categories7","categories8","categories9","categories10","categories11","categories12","categories13","categories14","categories15","categories16","categories17","categories18"),sep = ";")
first_encod %>% separate(categories, c("categories1", "categories2","categories3","categories4","categories5","categories6","categories7","categories8","categories9","categories10","categories11","categories12","categories13","categories14","categories15","categories16"),sep = ";")## Warning: Expected 16 pieces. Additional pieces discarded in 9 rows [451, 1244,
## 1326, 1419, 1808, 2693, 5149, 5851, 5947].## Warning: Expected 16 pieces. Missing pieces filled with `NA` in 8700 rows [1, 2,
## 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].#first_encod %>% separate(categories, c("A", "B"),sep = ";")
#separate(
# first_encod,
# col,
# into,
# sep = ";",
# remove = TRUE,
# convert = FALSE,
# extra = "warn",
# fill = "warn",
#)separate collapsed column to muitiple column:platforms
first_encod %>% separate(platforms, c("windows", "mac","linux"),sep = ";")## Warning: Expected 3 pieces. Missing pieces filled with `NA` in 7175 rows [1, 2,
## 3, 4, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 17, 18, 19, 20, 21, 22, ...].separate collapsed column to muitiple column:genres
first_encod %>% separate(genres, c("genres1", "genres2","genres3","genres4","genres5","genres6","genres7","genres8","genres9","genres10","genres11"),sep = ";")## Warning: Expected 11 pieces. Additional pieces discarded in 2 rows [957, 6378].## Warning: Expected 11 pieces. Missing pieces filled with `NA` in 8720 rows [1, 2,
## 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, ...].